Deep Learning for Automated Measurement of Patellofemoral Anatomic Landmarks

Background: Patellofemoral anatomy has not been well characterized. Applying deep learning to automatically measure knee anatomy can provide a better understanding of anatomy, which can be a key factor in improving outcomes. Methods: 483 total patients with knee CT imaging (April 2017–May 2022) from...

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Detalles Bibliográficos
Autores principales: Liu, Zelong, Zhou, Alexander, Fauveau, Valentin, Lee, Justine, Marcadis, Philip, Fayad, Zahi A., Chan, Jimmy J., Gladstone, James, Mei, Xueyan, Huang, Mingqian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10376187/
https://www.ncbi.nlm.nih.gov/pubmed/37508842
http://dx.doi.org/10.3390/bioengineering10070815

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10376187/
https://www.ncbi.nlm.nih.gov/pubmed/37508842
http://dx.doi.org/10.3390/bioengineering10070815

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